The biological cell may act as a parallel processing, non-linear, multistate, analog computer. This analog computer can occupy a volume of less than 10−16 m3 and is primarily powered only by sugars, fats, and oxygen. The complexity of these computers is evidenced by the attempts to model ongoing biochemical processes based on Mycoplasma genitalium, a microbe with the smallest known gene set of any self-replicating organism (http:\\www.e-cell.org). However, even this simplest model requires hundreds of variables and reaction rules, and a complete model even for a mammalian cell would be much more complex, requiring in excess of 105 variables and equations.
Because the cell behaves as an analog computer, it can be programmed. Historically, a limited set of interventions has allowed physiologists and engineers to study living cells and characterize the feedback control systems that govern cell function. With the advent of genetic engineering, it is now possible to reprogram the genetic machinery of a cell, for example to turn a particular gene on or off, or to produce large quantities of a particular biochemical. However, there has been little efforts and progress for inserting man-made devices into the control system of a single living cell so as to convert the cell into a programmable computational engine.
Therefore, among other things, there is a need to merge cellular biophysics, microcircuits and microfluidics, and information technology to create, among other things, programmable microsystems that can be used for sensing, feedback, control and analysis of a single cell and/or an array of interconnected and instrumented living cells.
Additionally, current bio-sensors use biological molecules for specific agent detection via specific binding reactions. However, wide-spectrum detection is expensive, requiring a priori threat knowledge and a large quantity of specific cells. Assays are susceptible to overload from multiple threats and false detection and from non-pathogenic “spoof” organisms. Furthermore, addressing new threats involves a lengthy, costly design process. In addition, conventional assays lack cellular machinery to increase sensitivity.
Therefore, among other things, there is also a need to develop new systems and methods that are capable of providing a complete bio-functional signature of a CBW agent, environmental contaminant, unknown drug, or other threats for better, fast, sensitive accurate and efficient detection.